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AI To Spot Legal Problems in the Companies

Researchers at the European University Institute in Florence are working on the project that aims at the application of machine learning technology to significantly sift big tech’s privacy policies. The research team from Europe is operational to find out if AI is able to automatically spot violations of data protection law.

The underway privacy policies and contract analyzing tool, “Claudette”: Aka (automated) clause detector, is developed by the research scientists.

Now, BEUC, a consumer organization from Europe, has supported the recent project. It will be supporting the research team for a project named “Claudette meets GDPR”. The project particularly applies the tool to estimate compliance with the General Data Protection Regulation of EU.

Recently, the project results are released by the scientists. BEUC proclaimed that the AI was successful to highlight a variety of problems automatically with the language being used in tech T&Cs during the research study.

Researchers employed Claudette in about 14 companies. It will analyze the privacy policies in these companies. Google, Facebook (and Instagram), Amazon, Apple, and Microsoft are some of the companies who have participated in the research study. Researchers proclaimed that the project selected these companies to cover a range of online services and sectors.

On a related note, Baidu recently revealed its AI-based chip, Kunlun. The company announced this product launch at the annual “Baidu Create event” on Tuesday. With the recent launch, Baidu has joined a drive of other Chinese firms to design the hardware that is tailored for machine-learning.

Kunlun is optimized for various tasks with the help of AI. Voice recognition, natural language processing, image recognition, and autonomous driving are some of the tasks that can be done using Kulun. The recent design is about 30 times faster than the original FPGA-based processor. However, the company has proclaimed that presently it will not begin the mass producing of the product.

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